Advanced visualization provides image archive challenge
The use of large image datasets with advanced visualization capabilities has demonstrated great clinical utility; however, the increase in near-isotropic image datasets presents a non-trivial data management and informatics challenge for PACS administrators, according to Paul J. Chang, MD.

Chang, professor and vice-chairman of radiology informatics as well as medical director of pathology informatics at the University of Chicago School of Medicine, and medical director of enterprise imaging at the University of Chicago Hospitals, offered his thoughts on advanced visualization archive strategies in a presentation at last month’s Digital Healthcare Information Management System (DHIMS) conference in San Antonio, Texas.

He noted that there is a definite trend toward on-demand archive design, with less emphasis on hierarchical storage models.

“The penalty for migration of very large datasets from slower media is increasingly unacceptable,” he said.

Users of advanced visualization tools want on-demand study retrieval across the image enterprise. System administrators seeking to meet the advanced visualization archive challenge have six models, with variations, from which to select, according to Chang. Each model has advantages and disadvantages that need to be considered before determining which schema best meets the needs of an institution.

The Selective Archive model has the advantages of being trivial to implement and permanently stores only “thick” slices, which is the least demanding on PACS archive storage requirements, Chang said. However, because only stored key images are available, it is not able to use interactive advanced visualization on prior or even relatively recent studies.

“It’s not able to take full advantage of future visualization and analysis tools on prior studies,” he noted.

A Selective Archive model with temporary cache strategy will allow the use of interactive advanced visualization on al current and relatively recent prior studies, depending on the size of the cache, Chang said. The downside is that once the prior studies are no longer resident in the temporary cache, these tools are not able to be used.

A Complete Dataset model permanently stores both thick and think slices, which allows for advanced visualization technology to be used on all current and prior studies. The disadvantage is that this greatly increases the PACS permanent archive storage requirements, Chang noted.

“Storing both thick and thin slices within a PACS archive is wasteful and redundant,” he said.

A Complete Dataset model with a Pseudo-Integrated Workstation scheme provides the advantage of making advanced visualization tools available via a “plug-in” and is less disruptive to normal workflow, Chang observed. Like the previous model, the drawback to this schema is that it calls for the storage of both thick and thin slices.

A Complete Dataset archive with an integrated workstation model permanently stores thin slices, which permits the use of advanced visualization components on all current and prior studies. Integrated tools in the workstation provides convenience to the interpreting physician and supports workflow requirements, and the architecture eliminates the inefficiency of storing redundant thick slices, Chang said. The disadvantage is that it increases the PACS permanent archive storage requirements, he noted.

The Complete Dataset archive with thin-client/server communication model holds the most advantages, according to Chang.

He said that it permanently stores thin slices, allowing the use of current and future advanced visualization software on prior and current studies; it supports workflow requirements; it allows for automated generation and transmission of thin slices; it reduces hardware and network requirements for workstations; it can improve client-workstation performance; and it allows for the utilization of full-featured advanced visualization tools via web viewers. However, it does increase PACS archive storage requirements.

The need for more storage to meet advanced visualization demands may not play as negative a role as one might think, primarily due to technology advances and the effect of economy of scale influences on the image archive market space.

“Current and even near-future storage requirements for large image datasets track reasonably well with continuously improving technical and economic efficiencies related to mass storage,” Chang noted. “These trends have significantly influenced archive persistence models for large image datasets.”